Revolt BI s.r.o

Demand forecasting using data science techniques simplifies the client’s warehouse operations and goods flow.Baseline situationA leading sports equipment retailer with nearly 200 brick-and-mortar stores and an e-shop needed to forecast demand for goods that were highly subject to various influences, especially weather fluctuations, which complicated warehouse operations. ‍ Our approachRevolt BI created a predictive model that predicts the turnover of specific goods at SKU level in all branches and in the e-shop with an accuracy of 80-90%. This allows for optimization of intralogistics operations, particularly stock placement, picking and preparing merchandise for surges in demand. Achieved successWith the help of demand forecasting, it was possible to optimize intralogistics processes to such an extent that the time spent picking goods was reduced, the planning of warehouse operational resources was improved and the overall labor intensity of warehouse operations decreased by 10%.

Client, a pet supply company with an e-shop and 150+ stores , faced financial challenges and lacked transparency in inventory and sales data. Crisis manager sought help from Revolt BI to revitalize the company. Facing outdated systems and data integration issues, our quick and targeted response included creating a robust data pipeline, implementing Keboola and Tableau, and enhancing clients internal team’s Tableau skills. Over two years, the collaboration resulted in significant improvements, enabling client to make informed decisions and achieve operational efficiencies.